Clinical cancer treatment aims to target all cell subpopulations within a tumor. Autofluorescence microscopy of the metabolic cofactors NAD(P)H and FAD has shown sensitivity to anti-cancer treatment response. Alternatively, flow cytometry is attractive for high throughput analysis and flow sorting. This study measures cellular autofluorescence in three flow cytometry channels and applies cellular autofluorescence to sort a heterogeneous mixture of breast cancer cells into subpopulations enriched for each phenotype. Sorted cells were grown in culture and sorting was validated by morphology, autofluorescence microscopy, and receptor expression. Ultimately, this method could be applied to improve drug development and personalized treatment planning.
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